Growth Analytics Associate

Commercial Strategy & Analytics Associates are YouLend’s analytical problem solvers. You will work on the questions that sit between Commercial, Product, Risk, Pricing and Data: how we set offers, how we test changes, how we improve conversion, how we optimise renewals, how we use partner data better, and how we make smarter decisions across the funding journey. This is a hands-on analytical role.

You will use SQL, Excel / Sheets and Python or similar tools to get underneath the hood, understand what is really happening, design tests, build models, and turn messy data into clear recommendations. You are not expected to be a software engineer. But you do need to be technical enough to follow the thread from a commercial question into the data, product flows, decisioning logic or configuration, and back to a practical answer that teams can act on.

What you'll be doing Designing and running commercial experiments: define the hypothesis, agree success metrics, monitor results and recommend the next action. Analysing growth opportunities across offers, pricing, eligibility, renewals, customer journeys and partner performance. Using SQL, Excel / Sheets and Python or similar tools to understand what is driving performance.

Building models to size opportunities and assess trade-offs across conversion, funded amount, risk, pricing, margin and customer experience. Improving the data foundations behind commercial decision-making: funnel tracking, event definitions, metric quality and test measurement. Working with Product, Risk, Pricing and Data to turn analysis into product changes, decisioning logic, tests or operational improvements.

Building lightweight proof-of-concepts, dashboards, scripts or AI-assisted tools where they help validate an idea quickly. Translating technical analysis into clear recommendations that Commercial, Product, Risk and senior stakeholders can act on. Example Problems How should we set renewal eligibility to maximise incremental funding while protecting risk and unit economics?

A pricing, eligibility or journey change looks promising. How do we design a test that tells us whether it actually improves outcomes? Which customer segments should receive different offer structures based on conversion, repayment behaviour, profitability and customer experience?

Where are automated offers underperforming manual review, and what logic or journey changes would close the gap? How can we use partner data more effectively to improve targeting, decisioning, pricing or conversion? What lightweight tool, dashboard or AI prototype could help Commercial teams answer a recurring question faster?

What you'll need 2-4 years’ experience in analytics, strategy, consulting, fintech, product analytics, engineering or another role that blends analytical and commercial problem-solving. Strong SQL skills and excellent Excel / Google Sheets ability. Python or similar coding ability.

Strong analytical judgement: you can work with messy data, spot issues, test assumptions and explain what the numbers really mean. Commercial curiosity: you care about growth, conversion, pricing, risk, customer experience and unit economics. Interest in experimentation, including A/B tests, holdouts, success metrics and how to measure impact properly.

Comfort getting into technical detail: product flows, data models, documentation, logic, configuration and how decisions are actually made. Strong communication skills. You can explain technical analysis to non-technical audiences and turn it into a clear recommendation.

A self-directed working style. You are comfortable with ambiguity, imperfect data and fast-moving priorities. Bias toward action.

You do not just analyse problems; you help get solutions tested, shipped or handed off properly. Helpful but not required Experience in fintech, lending, payments or embedded finance. Understanding of lending or MCA unit economics, including pricing, repayment behaviour, losses, opex and capital constraints.